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This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

This study aims to examine whether there are differences between financial statements prepared in accordance with International Financial Reporting Standards (IFRS) and financial statements prepared in accordance with local accounting standards in terms of its ability to present the financial conditions of companies listed on the Saudi Stock Exchange as one of the emerging markets.

Data on study variables were obtained from the published financial statements of 67 of listed companies in the Saudi Stock Exchange during the period 2014–2019. The study addressed the research hypotheses by using Altman Z-score model. Both the T-test and Wilcoxon rank test were used to investigate the significance of differences between the values of Z-score and the individual variables included in the model in the pre- and post-IFRS mandatory adoption periods.

The results revealed a decrease in the values of Z-score as well as the values of the individual variables included in the model in the period following the adoption of IFRS than it was before the adoption of IFRS, which indicates the ability of IFRS to show the financial conditions of companies more transparently than local accounting standards. However, the results of the T-test and Wilcoxon test showed that these decreases were not statistically significant.

This study has some limitations, including the small sample size as a result of the small size of the Saudi Stock Exchange, As well as the reliance of this study only on the Altman model with its five variables in assessing financial conditions without examining the impact of other factors that may affect the financial conditions of companies.

Financial conditions of the companies have important implications for multiple parties such as management, government, investors and others as an early warning sign that enables them to take the necessary measures early before the actual bankruptcy occurs and what results in costs.

Although assessing financial conditions of the companies is one of the basic uses of accounting information, this topic has not received sufficient attention as a means to test the benefits of adopting IFRS, especially in emerging markets such as Saudi Stock Exchange. This is the first study to examine the impact of adopting IFRS on the transparency of financial reporting in assessing financial conditions in Saudi Arabia.

This paper aims to synthesize the diverse literature on nomination and remuneration committees and provide avenues for future research.

This study provides a comprehensive literature review of theoretical and empirical studies published in reputable international journals indexed by Scopus.

The literature review reveals several aspects of the nomination and remuneration committee. These aspects have been classified into the definition of the nomination and remuneration committee, dimensions of the nomination and remuneration committee, measurement and research review results, reasons for conflict empirical findings, company dynamics and research on moderators, as well as recommending future research.

Our literature review shows that nomination and remuneration committees play a role in improving board performance and company performance, reducing agency conflicts and improving corporate governance to provide implications for companies, regulators and investors and pave the way for future research.

This paper identifies issues related to nomination and remuneration committees, their theoretical and practical implications and avenues for future research.

The purpose of this research is to examine the impact of governance mechanisms on corporate failure.

This study used a hypothesis-testing research design to collect data from the annual reports of 35 companies listed on Palestine Exchange from 2010 to 2019. Descriptive and inferential statistics were employed, along with correlation analysis to evaluate linear relationships between variables. The variance inflation factor was used to test multicollinearity, and binary logistic regression was utilized to develop the research model.

There is a significant positive relationship between board of directors' independency, institutional ownership and the quality of external audit, and corporate failure reduction. No significant relationship has been found among corporate governance variables such as board size, board meetings' frequency, board members' remuneration and audit committee existence, and corporate failure reduction.

Several empirical research studies have developed models to predict corporate failure using accounting and financial data. However, limited research has empirically investigated the impact of the different mechanisms of governance on corporate failure prediction.

The research highlighted the significance of companies' commitment to governance principles and their impact on predicting failure. The study suggests that decision-makers and managers can adopt different governance mechanisms to support corporate success and avoid those that may lead to negative consequences and failure.

This research is the first in Palestine to use a comprehensive list of corporate governance mechanisms to predict the failure of companies listed on the Palestine Stock Exchange between 2010 and 2019.

Ergonomics usually reciprocate the study about people fitness toward working environment. In addition, financial distress refers a condition of organizations incompetency in generating sufficient revenues or incomes, which thereby refrain them to pay their financial obligations. This study aims to evaluate two independent organizational fields named as ergonomics in first phase and financial distress in manufacturing organization behavior in the second phase. The study presented a resiliency framework for operations and strategic management in the third phase based on various facts received from the distress organizations.

A questionnaire survey based on plant-visit is presented. The study embedded two segments to explicate its novelty. In the first segment, the plant-visit case study is presented and in the second segment, an exploratory data related to financial distress is presented. The study tried to communicate observations related to multiple decision-making fields in single umbrella, where multiple concepts like ergonomics and financial distress of organizations as well as employees are presented. DEMATEL-ANP integrated approach is used to represent the critical financial distress dimensions of employees and their ranking.

The study provided insights toward connecting two independent fields named as ergonomics and financial distress in single umbrella. The study can benefit practitioners in designing policies and procedures in their planning model to effectively achieve organizational goals. The study presented 14 financial distress drivers of employees and advocated the aggregation of ergonomics and financial distress toward developing a holistic framework for attaining organization goals for sustainability.

The study presented a comprehensive understanding about multiple organization decision-making fields toward developing a holistic approach from different aspects for attaining organizational sustainability. The study can be fruitful in stimulating cross-pollination of ideas between researchers and provides a good understandability of ergonomics and financial distress in single roof.

Sustainability is essential to the ongoing operations of banks, though it is much less clear how Islamic corporate governance (ICG) promotes economic sustainability (ES) and thereby prevents bankruptcy. To explore the unexplored, this study aims to examine the efficacy of ICG in preventing bankruptcy and enhancing the ES of Islamic banks operating in Pakistan.

The current study measures ES through Altman's Z-score to analyze the level of the industry's stability and consequently examines the effect of ICG on the ES of Islamic banks in Pakistan for the post-financial-crises period. Using the country-level data, this study utilized a fixed-effect model and two-stage least squares (2SLS) techniques on balanced panel data spanning from 2009 to 2020 to provide empirical evidence.

The empirical results unveiled that board size and meetings have a significant positive influence on the ES while managerial ownership demonstrated an unfavorable effect on ES. Interestingly, the insignificant effect of women directors became significant with the inclusion of controlled variables. Overall, the findings indicate that ICG is an efficient tool for promoting ES in Islamic banks and preventing them from the negative effects of emerging crises.

The findings provide concrete insights for policymakers, regulators and other concerned stakeholders to execute a sturdy corporate governance system that not only oversees the economic, social and ethical aspects but also provides measures to alleviate the impacts of potential risks like the COVID-19 pandemic.

Examining the role of ICG in alleviating bankruptcy risk is an informative and useful endeavor for all social actors.

To the best of the authors’ knowledge, this study is one of the first efforts to provide evidence-based insights on the role of ICG in preventing bankruptcy and offers a potential research direction for ES.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

This study aims to examine the impact of intellectual capital (IC) on default risk in Indian companies listed on the National Stock Exchange.

This study applies panel data regression analysis to derive a relationship between IC and default risk for the sample period 2013–2022. The value-added intellectual coefficient (VAIC) of Pulic (2000) has been applied to measure IC performance, and default risk is estimated using the revised Z-score model of Altman (2000).

The results revealed a positive association between Z-score and VAIC. It implies that a higher value of VAIC improves financial stability and leads to a lower likelihood of default. The findings further suggest that new default forecasting models can be experimented with IC indicators for better default prediction.

The findings can have implications for investors and banks. This paper provides evidence of IC performance in improving the financial solvency of firms. Investors and financial institutions should invest their resources in a healthy firm that effectively manages and invests in their IC. It will eventually award investors and creditors high returns through efficient value-creation processes.

This study provides evidence of IC performance in improving the financial solvency of Indian high-defaulting firms, which lacks sufficient evidence in this domain of research. Numerous studies exist examining the relationship between firm performance and IC value, but this area is inadequately focused and underresearched. This study, therefore, fills the research gap from an Indian perspective.

This study aims to analyze the effect of cognitive load and social value orientation on managers’ preferences when they face with two types of restructuring choices in financially distressed firms: the first belonging to the family of organizational restructuring (massive layoffs) and the second to the family of financial restructuring (debt increases).

The authors investigate experimentally the impact of managers’ cognitive load and social value orientation on the decision to restructure leveraged buyout (LBO) firms in financial distress by using either massive layoffs or debt increases.

By investigating the impact of managers’ cognitive load and social value orientation on the restructuring decision of an LBO firm in financial distress, the research reveals that, on average, cognitively loaded managers prefer massive layoffs over increased debt levels. The massive layoffs seemingly provide a relatively easier way to avoid conflict with influential, residual claimants. In contrast, social value–oriented managers actively avoid massive layoffs and prefer to increase debt.

These results imply that the performance mechanisms emphasized to improve agency relations, for example, in LBOs, have their own limitations during periods of financial distress. This study shows that one of these limits is related to cognitive distortions and personality traits.

In this research, the originality lies in understanding how managers’ internal factors affect their restructuring decision-making, in the case of LBO firms in financial distress.

The objective of this study is to investigate the relationship between trade credit supply and financial distress outcomes, considering the role that trade credit plays as a substantial source of liquidity for distressed companies. Specifically, it examines whether there is an association between trade credit supply and the outcomes experienced by companies that undergo the voluntary administration (VA) insolvency procedure under Australian corporate law.

The study examines a sample of companies that were listed on the Australian Securities Exchange and entered VA between 2002 and 2019. Ordered logistic regression is used to determine the relation between trade credit and VA outcomes. The VA outcomes considered are as follows: (1) company liquidation, (2) orderly dissolution through an agreement with creditors, or (3) an agreement with creditors for reorganization of all or part of the company's business.

The findings show that trade creditors' willingness to supply credit is influenced by their rational expectations about the future prospects of financially distressed customers. Higher levels of trade credit and an increase in trade credit supply prior to VA are associated with a greater probability of achieving a reorganization versus a liquidation or dissolution outcome.

There is no apparent prior study investigating the connection between trade credit supply and outcomes for distressed companies entering insolvency administration. Therefore, this study provides novel evidence on the role of trade credit in the context of financial distress. Understanding the relationship between trade credit supply and outcomes is particularly significant considering that many jurisdictions offer distressed companies the opportunity to pursue reorganization under their insolvency laws. Examining financial distress and trade credit in the Australian creditor-friendly context expands on existing research. Prior research has predominantly relied on data from the United States, which has debtor-friendly bankruptcy law. Consequently, these studies may lack generalizability to jurisdictions with creditor-friendly law such as Australia.